AI Guides › Money & Business
Using AI To Find The Gap In Your Own Market, Not Just Ideas
By Nigel Guy · 2 min read
The default move is to ask AI for "business ideas in [industry]" and get back
a tidy, generic list — the same handful of suggestions anyone else asking the
same question would get, because it's drawing on the same broad training
rather than anything specific to your market. It reads like insight. It's
recycled.
The rule: AI is far more useful for spotting patterns in a market you
already know than for inventing one from nothing — feed it what you and your
customers actually see, and ask it to find the gap, not generate one.
The mechanism: the Complaint Audit
- Collect actual friction from your market — competitor reviews,
support tickets, forum threads, comments you've genuinely heard. Real
text, not your paraphrase of what people probably want.
- Feed a real sample to AI and ask it to group the complaints into
recurring themes, ranked by how often they show up. This is
pattern-spotting across volume you couldn't read through by hand — a
genuinely useful task for it.
- Cross-check the top themes against who already serves them. A real
gap is frequent, painful, and currently underserved. A theme where
someone already handles it adequately isn't a gap — it's a preference for
something better, which is a different and harder problem.
- Test the smallest recurring complaint yourself — a handful of direct
questions or messages to people who match the pattern — before building
anything.
- Note what your specific vantage point gives you that a cold AI ideas
list can't: an existing customer base, industry experience, access others
asking the same generic prompt don't have. That access is the actual
asset here, not the AI output.
What to skip
Skip asking for "the next big opportunity" cold, with no real data behind
it — that's the generic-list problem again, just with more words in the
prompt. Skip treating a ranked pain-point list as proven demand without
checking who's already serving it; frequency of complaint and willingness to
pay for a fix are related but not the same thing.
Guardrails
- Reviews and public complaints skew toward a loud, dissatisfied minority —
they're a starting signal, not a representative survey of your market.
- Verify at small scale before committing real time or money; a pattern in
complaint text is not the same as a validated willingness to pay.
- AI can tell you how often something is mentioned. It can't tell you
whether people would actually pay to fix it — that still needs a real
conversation or a real test.
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